I've searched for Statistical Programmer roles in Chicago, targeting the biotech industry, requiring 5+ years of experience, and proficiency in SAS programming, along with a bachelor's degree or higher. I found 27 positions available for you.

Sure. Here's the analysis:

Job Analysis:

The Statistical Programmer role at Katalyst CRO is fundamentally centered on ensuring the integrity and regulatory compliance of clinical trial data through expert SAS programming. The successful candidate will not only develop, validate, and maintain statistical programs but also adapt them in compliance with FDA and global health authorities' standards. This role involves the creation of SDTM domains while generating tables, listings, and figures essential for clinical study reports and regulatory submissions. Given the complex nature of clinical data, the programmer will face challenges such as maintaining high data quality standards and meeting tight deadlines, which requires both technical expertise and effective problem-solving skills. Success in this role will be measured not only by the accuracy of the outputs but also by the ability to document processes thoroughly and communicate findings clearly to cross-functional teams, illustrating the importance of collaboration in a dynamic environment.

Company Analysis:

Katalyst CRO operates in the highly specialized field of contract research and knowledge process outsourcing, positioning itself as a pivotal player in the healthcare and life sciences sectors. As a company committed to advancing innovative research and regulatory solutions, it emphasizes compliance and quality excellence, which are crucial to its client base of pharmaceutical, biotechnology, and medical device organizations. The culture at Katalyst is likely fast-paced and driven by a commitment to scientific rigor and client-centric solutions, which means that adaptability and proactive problem-solving are valued traits. The Statistical Programmer will be part of a team that directly contributes to critical stages of drug development, which not only highlights the role's influence within the organization but also reflects the company's strategic alignment of hiring talent capable of reducing risk and enhancing research programs. This role is essential for facilitating timely and successful regulatory submissions, demonstrating the importance of precision and reliability in the methods employed by Katalyst CRO.

Absolutely. Here are some mock interview questions that could come up:

• Tell me about a time when you had to handle a significant data discrepancy during a clinical trial. How did you resolve it?
• How do you ensure the statistical programs you develop are compliant with CDISC and regulatory standards?
• Can you describe a challenging statistical programming project you led? What were the outcomes?
• What measures do you take to validate the accuracy and integrity of statistical datasets?
• What is your approach to prepare for FDA electronic submissions? Can you walk us through your process?
• How do you optimize SAS programs for efficiency without compromising data quality?
• Describe your experience with creating ADaM datasets. What challenges have you faced?
• Imagine you are tasked with generating statistical outputs for a clinical study close to its submission deadline, but the data has several inconsistencies. How would you prioritize your tasks?
• Why are you interested in working at Katalyst CRO specifically? What excites you about our approach to advancing healthcare?
• How does your experience align with the mission and values of Katalyst CRO in improving global patient health?
• What trends do you see in clinical programming and regulatory compliance, and how do you keep up with them?
• What questions do you have about the projects or teams you might be working with at Katalyst CRO?
• What resources have you found most helpful for staying current with statistical software updates?
• Can you provide an example of when you had to collaborate with a cross-functional team? What was your role and contribution?
• What do you find most rewarding about working in statistical programming within the life sciences?